When viewing videos, such as to select certain desired segments, location can be a useful source of information for a variety of tasks. For example, a user may recall that a home video shot in a child's playroom contains a particular scene that the user wants to send to a relative, whereby it would be useful to quickly locate video segments (or representative images) of those videos taken in that location. In general, users may want to browse or search videos by location, annotate locations, and/or create location-specific compilations.
Location-based clustering algorithms attempt to assist users in such a task. However, one significant challenge for location-based clustering algorithms is the wide range of appearances that exist within a single location. For example, consider a video taken within the same room of a house. Depending on the viewpoint as to where each shot was captured, widely varying appearances are possible.